Case perspective: the number of rows, i.e. cases, with missing values.
Many analysis methods only use the rows that are fully observed: complete-case analysis.
The data are then listwise deleted.
datm %>%
is.na %>%
data.frame() %>%
mutate(n_miss = rowSums(.),
missing = ifelse(n_miss > 0, "rows with misings", "rows without missing")) %>%
group_by(missing) %>%
summarise(n = n(),
p = n/ 25)
> # A tibble: 2 x 3
> missing n p
> <chr> <int> <dbl>
> 1 rows with misings 10 0.4
> 2 rows without missing 15 0.6